Full-Stack Quantitative Finance
Winter Quarter
Instructor: Jeremy Bejarano
Syllabus
"Full Stack Quantitative Finance" is a hands-on course centered on a core set of fundamental tools common across financial computing and data science. That is, this course examines elements of the analytical pipeline, from data extraction and cleaning to exploratory analysis, visualization, and modeling, and finally, publication and deployment. It does so with the aim of teaching the tools and principles behind creating reproducible and scalable workflows, including build automation, dependency management, unit testing, the command-line environment, shell scripting, Git for version control, and GitHub for team collaboration. These skills are taught through case studies, each of which will additionally give students practical experience with key financial data sets and sources such as CRSP and Compustat for pricing and financials, macroeconomic data from FRED and the BEA, bond transactions from FINRA TRACE, Treasury auction data from TreasuryDirect, textual data from EDGAR, and high-frequency trade and quote data from NYSE. Prior experience at an intermediate level with Python and the PyData stack is assumed.
This course counts towards the Financial Computing concentration.